This paper addresses the problem of multitarget tracking using a network of mobile sensors with unknown positions. In contrast to commonly-used approaches which split the sensor localization and target tracking into two different sub-problems, we propose a holistic approach for joint localization and tracking. The theory of graphical models is used to describe the statistical relationship between sensors, targets, and measurements. To jointly infer the states of sensors and targets, we use the statistical processing of belief propagation.

Joint Multitarget Tracking and Dynamic Network Localization in the Underwater Domain

Brambilla M.;Nicoli M.;
2020

Abstract

This paper addresses the problem of multitarget tracking using a network of mobile sensors with unknown positions. In contrast to commonly-used approaches which split the sensor localization and target tracking into two different sub-problems, we propose a holistic approach for joint localization and tracking. The theory of graphical models is used to describe the statistical relationship between sensors, targets, and measurements. To jointly infer the states of sensors and targets, we use the statistical processing of belief propagation.
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
978-1-5090-6631-5
File in questo prodotto:
File Dimensione Formato  
CV_2020_ICASSP_NATO.pdf

Accesso riservato

Descrizione: Publisher's version full paper
: Publisher’s version
Dimensione 746.01 kB
Formato Adobe PDF
746.01 kB Adobe PDF   Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1145015
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 5
  • ???jsp.display-item.citation.isi??? 3
social impact